
where \(\Theta \in (0,1]\)  is the relaxation parameter. Note that choosing an appropriate relaxation parameter is crucial to get a great rate of convergence of the DNWR algorithm. In [1]}, the optimal relaxation parameter has been proven to be \(\Theta = 1/2\)  for \(\lambda _1=\lambda _2=\alpha _1=\alpha _2=1\) . If one uses the optimal relaxation parameter for 1D problems, two iterations are enough for subdomains of equal length.
